Explore the vast range of titles available.

Presents more than thirty full-page science maps, fifty data charts, a timeline of science-mapping milestones, and 500 color images, which serve as a sumptuous visual index to the evolution of modern science and as an introduction to \"the science of science\"--charting the trajectory from scientific concept to published results.

Although single-cell RNA sequencing studies have begun to provide compendia of cell expression profiles 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 – 9 , it has been difficult to systematically identify and localize all molecular cell types in individual organs to create a full molecular cell atlas. Here, using droplet- and plate-based single-cell RNA sequencing of approximately 75,000 human cells across all lung tissue compartments and circulating blood, combined with a multi-pronged cell annotation approach, we create an extensive cell atlas of the human lung. We define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 out of 45 previously known cell types and 14 previously unknown ones. This comprehensive molecular atlas identifies the biochemical functions of lung cells and the transcription factors and markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signalling interactions and immune cell homing; and identifies cell types that are directly affected by lung disease genes and respiratory viruses. By comparing human and mouse data, we identified 17 molecular cell types that have been gained or lost during lung evolution and others with substantially altered expression profiles, revealing extensive plasticity of cell types and cell-type-specific gene expression during organ evolution including expression switches between cell types. This atlas provides the molecular foundation for investigating how lung cell identities, functions and interactions are achieved in development and tissue engineering and altered in disease and evolution. Expression profiling on 75,000 single cells creates a comprehensive cell atlas of the human lung that includes 41 out of 45 previously known cell types and 14 new ones.

Presents more than thirty full-page science maps, fifty data charts, a timeline of science-mapping milestones, and 500 color images, which serve as a sumptuous visual index to the evolution of modern science and as an introduction to \"the science of science\"--charting the trajectory from scientific concept to published results.

Soil bacteria play key roles in regulating terrestrial carbon dynamics, nutrient cycles, and plant productivity. However, the natural histories and distributions of these organisms remain largely undocumented. Delgado-Baquerizo et al. provide a survey of the dominant bacterial taxa found around the world. In soil collections from six continents, they found that only 2% of bacterial taxa account for nearly half of the soil bacterial communities across the globe. These dominant taxa could be clustered into ecological groups of co-occurring bacteria that share habitat preferences. The findings will allow for a more predictive understanding of soil bacterial diversity and distribution. Science , this issue p. 320 Relatively few soil bacterial taxa dominate terrestrial ecosystems worldwide, with predictable distributions and ecology. The immense diversity of soil bacterial communities has stymied efforts to characterize individual taxa and document their global distributions. We analyzed soils from 237 locations across six continents and found that only 2% of bacterial phylotypes (~500 phylotypes) consistently accounted for almost half of the soil bacterial communities worldwide. Despite the overwhelming diversity of bacterial communities, relatively few bacterial taxa are abundant in soils globally. We clustered these dominant taxa into ecological groups to build the first global atlas of soil bacterial taxa. Our study narrows down the immense number of bacterial taxa to a “most wanted” list that will be fruitful targets for genomic and cultivation-based efforts aimed at improving our understanding of soil microbes and their contributions to ecosystem functioning.

Single-cell molecular profiling technologies are gaining rapid traction, but the manual process by which resulting cell types are typically annotated is labor intensive and rate-limiting. We describe Garnett, a tool for rapidly annotating cell types in single-cell transcriptional profiling and single-cell chromatin accessibility datasets, based on an interpretable, hierarchical markup language of cell type-specific genes. Garnett successfully classifies cell types in tissue and whole organism datasets, as well as across species.

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

The mammalian brain consists of millions to billions of cells that are organized into many cell types with specific spatial distribution patterns and structural and functional properties 1 – 3 . Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4.3 million cells using multiplexed error-robust fluorescence in situ hybridization (MERFISH). The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters. We present an online platform, Allen Brain Cell Atlas, to visualize the mouse whole-brain cell-type atlas along with the single-cell RNA-sequencing and MERFISH datasets. We systematically analysed the neuronal and non-neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell-type organization in different brain regions—in particular, a dichotomy between the dorsal and ventral parts of the brain. The dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. Our study also uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types. Finally, we found that transcription factors are major determinants of cell-type classification and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole mouse brain transcriptomic and spatial cell-type atlas establishes a benchmark reference atlas and a foundational resource for integrative investigations of cellular and circuit function, development and evolution of the mammalian brain.  A transcriptomic cell-type atlas of the whole adult mouse brain with ~5,300 clusters built from single-cell and spatial transcriptomic datasets with more than eight million cells reveals remarkable cell type diversity across the brain and unique cell type characteristics of different brain regions. 

Single-cell RNA sequencing data can unveil the molecular diversity of cell types. Cell type atlases of the mouse spinal cord have been published in recent years but have not been integrated together. Here, we generate an atlas of spinal cell types based on single-cell transcriptomic data, unifying the available datasets into a common reference framework. We report a hierarchical structure of postnatal cell type relationships, with location providing the highest level of organization, then neurotransmitter status, family, and finally, dozens of refined populations. We validate a combinatorial marker code for each neuronal cell type and map their spatial distributions in the adult spinal cord. We also show complex lineage relationships among postnatal cell types. Additionally, we develop an open-source cell type classifier, SeqSeek, to facilitate the standardization of cell type identification. This work provides an integrated view of spinal cell types, their gene expression signatures, and their molecular organization. Single-cell profiling has led to the identification of diverse cell types. Here, the authors generate a harmonized cell atlas of the mouse post-natal spinal cord. They also provide spatial analysis of the distribution of the identified cell types and an open-source cell type classifier.

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals 1 . Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations. An examination of motor cortex in humans, marmosets and mice reveals a generally conserved cellular makeup that is likely to extend to many mammalian species, but also differences in gene expression, DNA methylation and chromatin state that lead to species-dependent specializations.

While our knowledge about the roles of microbes and viruses in the ocean has increased tremendously due to recent advances in genomics and metagenomics, research on marine microbial eukaryotes and zooplankton has benefited much less from these new technologies because of their larger genomes, their enormous diversity, and largely unexplored physiologies. Here, we use a metatranscriptomics approach to capture expressed genes in open ocean Tara Oceans stations across four organismal size fractions. The individual sequence reads cluster into 116 million unigenes representing the largest reference collection of eukaryotic transcripts from any single biome. The catalog is used to unveil functions expressed by eukaryotic marine plankton, and to assess their functional biogeography. Almost half of the sequences have no similarity with known proteins, and a great number belong to new gene families with a restricted distribution in the ocean. Overall, the resource provides the foundations for exploring the roles of marine eukaryotes in ocean ecology and biogeochemistry. Marine microbial eukaryotes and zooplankton display enormous diversity and largely unexplored physiologies. Here, the authors use metatranscriptomics to analyze four organismal size fractions from open-ocean stations, providing the largest reference collection of eukaryotic transcripts from any single biome.